迭代奇异值分解降噪与关联维数在烟气轮机故障诊断中的应用  

Application of ISVD de-noising and correlation dimension in fault diagnosis of flue gas turbine

作　　者：王浩[1] 张来斌[1] 王朝晖[1] 梁伟[1] 段礼祥[1] 

机构地区：[1]中国石油大学机电工程学院,北京102249

出　　处：《中国石油大学学报（自然科学版）》2009年第1期93-98,108,共7页Journal of China University of Petroleum(Edition of Natural Science)

基　　金：国家'863'资助(2008AA06Z209);教育部新世纪优秀人才支持计划(NCET-05-0110);石油科技中青年创新基金(07E1005);中国石油天然气集团公司创新基金

摘　　要：烟气轮机的振动信号具有很强的非线性特征。提出了将迭代奇异值分解(ISVD)降噪与关联维数分析相结合应用于烟气轮机故障诊断。采用低通数字滤波与ISVD降噪两种方法对实测数据进行降噪处理,对其效果进行对比,并计算烟气轮机在不同故障状态下振动信号降噪前、后的关联维数。结果表明:对于烟气轮机信号,低通数字滤波的降噪效果并不理想,而ISVD降噪则能有效地去除噪声;降噪后,烟气轮机振动信号的伪相图特征清晰,关联积分曲线的标度区明显变宽;不同故障状态下计算得到的关联维数明显不同,可以将关联维数作为故障诊断的定量特征进行提取,从而为烟气轮机故障诊断提供简单而有效的方法。Considering the complicated and non-linear characteristics of the vibrational signal of flue gas turbine, the iterative singular value decomposition （ISVD） de-noising and correlation dimension were applied in fault diagnosis of flue gas turbine. To eliminate the noise, the low-pass filter and the ISVD de-noising were applied separately. Then the correlation dimensions of vibration signal of flue gas turbine under different fault conditions were estimated. The results show that the effect of the low- pass filter is not obvious while the ISVD de-noising can reduce noise effectively. Comparing with the pseudo-phase portrait reconstructed from signal containing noise, the pseudo-phase portrait reconstructed after ISVD de-noising is more regular. By ISVD de-noising, the scale region on the log-log plot of correlation integrals becomes wider. The correlation dimension is obviously different for different fault conditions after ISVD de-noising, so it can be used as the quantitative characteristic parameter for fault diagnosis. This offers a simple and effective method for fault diagnosis of flue gas turbine.

关 键 词：烟气轮机 故障诊断 关联维数 ISVD降噪 伪相图 低通滤波 

分 类 号：TK268.1[动力工程及工程热物理—动力机械及工程] TE969[石油与天然气工程—石油机械设备]